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Recently, the Frank-Wolfe optimization algorithm was suggested as a procedure to obtain adaptive quadrature rules for integrals of functions in a reproducing kernel Hilbert space (RKHS) with a potentially faster rate of convergence than Monte Carlo integration (and "kernel herding" was shown to be a special case of this procedure).
An algorithm for quadratic programming
M. Frank and P. Wolfe · 1956
Earlier work this paper cites.
Convergence rates for conditional gradient sequences generated by implicit step length rules
J. C. Dunn · 1980
Earlier work this paper cites.
Summing and nuclear norms in Banach space theory
G. J. O. Jameson · 1987
Earlier work this paper cites.
Novel approach to nonlinear/non-Gaussian Bayesian state estimation
N. J. Gordon, D. J. Salmond, and A. F. M. Smith · 1993
Earlier work this paper cites.
Improved particle filter for nonlinear problems
J. Carpenter, P. Clifford, and P. Fearnhead · 1999
Earlier work this paper cites.
Filtering via simulation: Auxiliary particle filters
M. K. Pitt and N. Shephard · 1999
Earlier work this paper cites.
On sequential Monte Carlo sampling methods for Bayesian filtering
A. Doucet, S. J. Godsill, and C. Andrieu · 2000
Earlier work this paper cites.
Quasi-random sampling for condensation
V. Philomin, R. Duraiswami, and L. Davis · 2000
Earlier work this paper cites.
Mixture Kalman filters
R. Chen and J. S. Liu · 2000
Earlier work this paper cites.
Lattice particle filters
D. Ormoneit, C. Lemieux, and D. J. Fleet · 2001
Earlier work this paper cites.
Beyond the Kalman filter: particle filters for tracking applications
B. Ristic, S. Arulampalam, and N. Gordon · 2004
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Reproducing Kernel Hilbert Spaces in Probability and Statistics
A. Berlinet and C. Thomas-Agnan · 2004
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Inference in Hidden Markov Models
O. Cappé, E. Moulines, and T. Rydén · 2005
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Using random quasi-Monte-Carlo within particle filters, with application to financial time series
P. Fearnhead · 2005
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A Hilbert space embedding for distributions
A. Smola, A. Gretton, L. Song, and B. Schölkopf · 2007
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Particle filter SLAM with high dimensional vehicle model
D. Törnqvist, T. B. Schön, R. Karlsson, and F. Gustafsson · 2009
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On the equivalence between herding and conditional gradient algorithms
F. Bach, S. Lacoste-Julien, and G. Obozinski · 2012
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A kernel two-sample test
A. Gretton, K. M. Borgwardt, M. J. Rasch, B. Schölkopf, and A. Smola · 2012
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Optimally-weighted herding is Bayesian quadrature
F. Huszár and D. Duvenaud · 2012
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Handbook of mathematical functions: with formulas, graphs, and mathematical tables
M. Abramowitz and I. A. Stegun · 2012
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Learning with submodular functions: A convex optimization perspective
F. Bach · 2013
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Revisiting Frank-Wolfe: Projection-free sparse convex optimization
M. Jaggi · 2013
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Super-samples from kernel herding
Y. Chen, M. Welling, and A. Smola · 2010
Cited alongside, same era.
Hilbert space embeddings and metrics on probability measures
B. K. Sriperumbudur, A. Gretton, K. Fukumizu, B. Schölkopf, and G. R. Lanckriet · 2010
Cited alongside, same era.
A tutorial on particle filtering and smoothing: Fifteen years later
A. Doucet and A. Johansen · 2011
Cited alongside, same era.
New analysis and results for the Frank-Wolfe method
R. M. Freund and P. Grigas · 2013
Later among the works it cites.
Long-term stability of sequential Monte Carlo methods under verifiable conditions
R. Douc, E. Moulines, and J. Olsson · 2014
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M. Gerber and N. Chopin · 2014
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